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About the Role

The Analyst, Business Systems, is responsible for investing in new infrastructure projects. This role sits at the intersection of business strategy, data engineering, analytics and platform architecture, ensuring business requirements are translated into scalable, governed and trusted Microsoft Fabric-based data products. The analyst will work across the full delivery lifecycle, ensuring data products meet quality, security, governance and performance expectations.

Responsibilities

Lead discovery and analysis sessions to understand business objectives, reporting needs, KPIs and operational processes
Translate business needs into Epics, features and user stories, functional and non-functional requirements, and clear acceptance criteria aligned to data outcomes
Develop and maintain key artifacts: Business and data requirements documentation, process flows and use cases, business glossaries and metric definitions
Serve as the primary liaison between business stakeholders and Fabric delivery teams
Define and document source-to-target mappings, transformation logic and business rules, and data lineage and traceability across Fabric workloads
Support design and delivery across Fabric workloads, including data engineering, data warehouse, and real-time analytics
Ensure self-service reporting adheres to enterprise data governance standards, security, privacy and access controls, and metric consistency across domains
Partner with governance teams to maintain business glossaries and metadata, ensure discoverability through Microsoft Purview, and help prevent metric duplication and “multiple versions of the truth” by enforcing standardized definitions and datasets
Support AI and machine learning initiatives through data preparation, feature engineering, validation, and performance monitoring
Evaluate the effectiveness of AI-enabled solutions and recommend continuous improvements

Requirements

Experience with data modelling: Dimensional modelling, transactional vs. analytical data structures, data grain and aggregation strategies
Experience contributing to enterprise data warehouse design, including subject-area modelling, historical data handling, and data retention and archival strategies
Understanding of query performance considerations from a modelling perspective, partitioning and summarization concepts, and ability to assess downstream reporting impact of modelling decisions
Experience with Microsoft Fabric, including Lakehouse and/or warehouse, Data Factory pipelines, Notebooks (Spark), and OneLake architecture
Two to four years of experience in data analysis and reporting, preferably with Power BI
Ability to work independently with excellent organizational and priority management skills
Knowledge of AI/ML architectures, Generative AI, LLMs, vector databases, and MLOps/LLMOps practices
Strong proficiency in DAX, Power Query (M) and data modelling concepts
Strong SQL skills and experience with data modelling for analytics
Good understanding of ETL processes and data warehousing principles
Knowledge of Azure services (Data Lake, Synapse, Data Factory, etc.)
Familiarity with CI/CD for data pipelines (Azure DevOps, Git)
Familiarity with governance and security best practices in Power BI
Excellent analytical and problem-solving skills
Strong written and verbal communication skills with the ability to interact with technical and non-technical stakeholders
Sense of initiative, entrepreneurial spirit
Experience in agile methodologies and project management

Skills

Microsoft Fabric
Data modelling
Dimensional modelling
Transactional vs. analytical data structures
Data grain and aggregation strategies
Enterprise data warehouse design
Subject-area modelling
Historical data handling
Data retention and archival strategies
Query performance considerations
Partitioning and summarization concepts
Source-to-target mappings
Transformation logic
Business rules
Data lineage
Traceability
Data engineering
Lakehouse
Notebooks
Pipelines
Data warehouse
T-SQL analytics
Real-time analytics
Microsoft Fabric
Power BI
Power BI semantic models
Measures
Hierarchies
Relationships
Dataset reuse
Self-service enablement patterns
Certified and promoted datasets
Workspace design
Shared OneLake data products
Self-service BI and analytics concepts
DAX
Power Query (M)
ETL processes
Data warehousing principles
Microsoft Purview
Microsoft Power Platform (Power Apps, Power Automate)
Azure services (Data Lake, Synapse, Data Factory, etc.)
CI/CD for data pipelines
Azure DevOps
Git
Governance and security best practices in Power BI
AI/ML architectures
Generative AI
LLMs
Vector databases
MLOps/LLMOps practices

Location

Toronto

Work Type

Full-time

Experience Level

Three years of experience in data analysis and reporting
Two to four years of experience in a similar role
Two to four years of experience in data analysis and reporting, preferably with Power BI

Education Level

Undergraduate degree in information systems, business, finance, computer science or equivalent

About the Company

Headquartered in Toronto, the Canada Infrastructure Bank (CIB) is responsible for investing in new infrastructure projects.
The CIB’s mission is to work with provincial, territorial, municipal, federal, Indigenous and private sector investor partners to transform the way infrastructure is planned, financed and delivered in Canada.
For more information on our company, visit www.cib-bic.ca.

Equal Opportunity

At the CIB, we are committed to diversity and equitable access to employment opportunities. If you require an accommodation for the recruitment/interview process (including alternate formats of materials, or accessible meeting rooms or other accommodation), please let us know at accessible@cib-bic.ca and we will work with you to meet your needs.